RIFNOM: 3D Rotation-Invariant Features on Normal Maps

Akihiro Nakamura, Leo Miyashita, Yoshihiro Watanabe & Masatoshi Ishikawa
This paper presents 3D rotation-invariant features on normal maps: RIFNOM.We assign a local coordinate system (CS) to each pixel by using neighbor normals to extract the 3D rotation-invariant features. These features can be used to perform interest point matching between normal maps. We can estimate 3D rotations between corresponding interest points by comparing local CSs. Experiments with normal maps of a rigid object showed the performance of the proposed method in estimating 3D rotations. We...
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